The present disclosure relates to computing and data processing, and in particular, to parallel computing without requiring antecedent code deployment.
Processing multiple computing tasks in parallel is important. First, computing resources that might otherwise be idle can be utilized, thereby increasing system efficiency. For example, computing resources already purchased from a cloud provider can be leveraged to expedite a sorting program, which could otherwise take longer to finish if executed entirely locally. Second, related programs may be executed in parallel, rather than in series, and their results provided to a user faster, thereby cutting system response time.
Difficulties abound, however. One of the technical problems is that, leveraging resources available at a remote computer might require local code libraries to be deployed well in advance. This may not be feasible all the time. For example, a local Java function library may need to be copied to and configured at a cloud system before the cloud system can execute relevant programs. This code deployment process, however, might require significant setup efforts by a system administrator and thus might not be available to a software engineer when needed.
There is therefore a need for improved techniques to parallel computing without requiring antecedent code deployment.